Threat detection plays a vital role in adapting behavior to changing environments. A fundamental function to improve threat detection is learning to differentiate between stimuli predicting danger and safety. Accordingly, aversive learning should lead to enhanced sensory discrimination of danger and safety cues. However, studies investigating the psychophysics of visual and auditory perception after aversive learning show divergent findings, and both enhanced and impaired discrimination after aversive learning have been reported. Therefore, the aim of this web-based study is to examine the impact of aversive learning on a continuous measure of visual discrimination. To this end, 205 participants underwent a differential fear conditioning paradigm before and after completing a visual discrimination task using differently oriented grating stimuli. Participants saw either unpleasant or neutral pictures as unconditioned stimuli (US). Results demonstrated sharpened visual discrimination for the US-associated stimulus (CS+), but not for the unpaired conditioned stimuli (CS−). Importantly, this finding was irrespective of the US’s valence. These findings suggest that associative learning results in increased stimulus salience, which facilitates perceptual discrimination in order to prioritize attentional deployment. Introduction Learning to detect threat-predicting stimuli is a fundamental function for supporting adaptive behavior in ever-changing environments. Recent theories propose that threat This might be problematic as longer procedures are more affected by the temporal dynamics of extinction learning. This is aggravated by the observation that threat-related visuocortical sharpening extinguishes rapidly 10 . To overcome these issues, we used a yes–no task to measure visual discrimination along a continuum of radial distance in steps of 1° before and after differential aversive learning. (3) To further test how discriminative learning impacts discrimination acuity, we included two further groups that did the same discrimination task as the differential learning groups but saw six additional generalization stimuli (GS) in 10° steps around the CS+ (− 30°, − 20°, − 10°, 10°, 20°, 30°; ) 10 during associative learning with either aversive or neutral US. Numbers indicate means (± S.D.). Materials Circular black-and-white sinusoidal grating stimuli (10 Hz spatial frequency) filtered with a Gaussian-envelope (i.e., Gabor-patch) with maximum contrast of 100% at center were used as conditioned stimuli for the conditioning procedure and as target stimuli for the visual discrimination task. Aversive and neutral picture stimuli served as unconditioned stimuli (US). All pictures were extracted from the OASIS data set 28 . The standard differential learning paradigm consisted of 40 CS+ presentations and 40 CS− presentations (80 trials in total). Crucially, the differential learning groups that were psychophysically tested on the CS− (cDiff+, cDiff−) completed the same learning task as the groups that were tested on the CS+ (Diff+ , Diff−). In contrast, the generalization learning groups (Gen+ , Gen−) were presented with 10 trials of each CS+ , CS− and six generalization stimuli (GS) in 10° steps around the CS+ (− 30°, − 20°, − 10°, 10°, 20°, 30°) 10 , also resulting in 80 total trials. For all groups, every CS+ presentation was followed by a presentation of an US (100% reinforcement rate), while the CS − (and all GS in generalization groups) remained unpaired. Importantly, five of the ten aversive picture stimuli served as US for the aversive learning groups (Diff+ , Gen+ , cDiff+), whereas five of the ten neutral picture stimuli were used as US for the neutral learning groups (Diff− , Gen− , cDiff −). The remaining five pictures of the same category were used in the US memory task at the end of the experiment. The choice of US was counter-balanced between participants. Therefore, the standard deviations of these distributions serve as an index of discrimination ability and the change of standard deviations can be used to measure the impact of associative learning on discrimination acuity. Extracted standard deviations were log-transformed to account for skewedness in the distribution of the data. Shapiro–Wilk tests of normality still indicated left-skewed distributions for the pre-task, w (205) = 0.981, p = 0.009. A significance level of 0.05 was used for all analyses and Greenhouse–Geisser correction was applied where appropriate 37 . Throughout this manuscript, corrected degrees of freedom, corrected p values and the partial η 2 ( η p 2 ) or Cohen’s d ( d ) and their 95% confidence interval are reported 38 . Results Discrimination task The 2 (learning type: differential vs. generalization learning) × 2 (aversiveness: neutral vs aversive US) × 2 (phase: pre vs. The ventral attention network, including the temporoparietal and inferior frontal cortices, is specialized on detecting behaviorally relevant, salient stimuli 53 . The results of our current study are well in line with the notion that the ventral attention network, activated by salient stimuli via associative learning, induces visuocortical tuning in orientation-specific neurons, which then leads to improved discrimination acuity in behavioral measures. Crucially, these changes do not depend on fear-relevant networks, which might be less activated by the neutral US used in the present study. 23 , demonstrating reduced discrimination thresholds for the CS+, but not for stimuli that were shifted by 90° relative to the CS+. The present study also included two further groups that did the same discrimination task as the differential learning groups but were presented with six additional generalization stimuli (GS) in 10° steps around the CS+ 10 during the associative learning paradigm. These participants experienced directly that only the CS+ was followed by an US, while all other GS, even those very similar to the CS+ , signaled safety.